Investigation of near-wall turbulence in relation to polymer rheology
Bibliographic record
Abstract
An experimental investigation was carried out to characterize the rheology of polyacrylamide solutions and its effect on the structure of a turbulent channel flow. The shear viscosity of 10 and 20 ppm solutions had similar magnitudes as that of water with a Newtonian behavior, while the 90 and 160 ppm solutions had a shear-thinning behavior. The elasticity and relaxation time of the solutions monotonously increased with an increase in polymer concentration. Pressure drop measurement at a Reynold number of 20 000 showed 25, 43, 51, and 57% drag reduction for 10, 20, 90, and 160 ppm solutions, respectively. Time-resolved planar particle image velocimetry was used to characterize the turbulent structure. The polymers were more effective in reducing the strain-rate in the buffer layer due to the larger strain rate and stretching of the polymers. This was consistent with larger values of the Weissenberg number in the buffer layer compared with the log layer. The distributions of the Weissenberg number showed two distinct distributions at the low and high drag reduction regimes. The addition of the polymers to the turbulent flow was observed to balance the local strain rate and rotation. This effect was observed in the inner layer for all polymer concentrations, while it was observed in the logarithmic layer only for the 90 and 160 ppm solutions. The power spectral density of turbulence kinetic energy in the buffer layer showed that the high frequency content was damped for the 10 and 20 ppm solutions, while a wider frequency range was attenuated at a higher polymer concentration.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".